n mix results

N - mixture models by species

modelling N by site to get relative abundance

abundance by site will be used as a cov on predator occupancy

7 models evaluated, dot, jdt + jdtSQ, lure + jdt + jdtSQ

Species:      WhiteTailedJackrabbit

Metadata Summary:

N_sites	N_counts	N_detections	rep_period	iterations	burnin	thin
127	283	181	7 days	120000	20000	10

Detections by Year:

Yr	2016	2017	2018	2019	2020
sites	19	31	19	32	26
detections	19	39	43	57	23
N.dot.model	7	17	19	18	7

WAIC

Models by WAIC:

model	description	WAIC	N.total.est
fm7	counts	3.962858	127
fm2	jdt	1116.837448	71
fm5	jdt + jdtSq	1117.412453	73
fm4	lure + jdt	1118.211814	72
fm6	lure + jdt + jdtSq	1118.662959	73
fm1	dot	1119.959703	68
fm3	lure	1119.983799	70

Model summaries:

model: fm1

dot

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
p[1]	NA	6368	0.113	0.108	0.06	0.16	0	1.001
p[2]	NA	4102	0.091	0.089	0.05	0.13	0	1.001
p[3]	NA	3343	0.052	0.05	0.03	0.07	0	1.001
p[4]	NA	5495	0.091	0.087	0.06	0.12	0	1.001
p[5]	NA	7630	0.081	0.078	0.05	0.11	0	1.001
lambda[1]	NA	6607	0.447	0.354	0.15	0.70	0	1.001
lambda[2]	NA	3939	0.767	0.643	0.39	1.12	0	1.001
lambda[3]	NA	3527	1.305	1.095	0.62	1.98	0	1.001
lambda[4]	NA	7079	0.687	0.636	0.38	0.98	0	1.001
lambda[5]	NA	8273	0.339	0.287	0.12	0.54	0	1.001
N[107]	NA	10000	0.024	err	0.00	0.00	err	err
N[12]	NA	10041	0.038	err	0.00	0.00	err	err
N[72]	NA	10000	0.102	err	0.00	0.00	err	err
N[21]	NA	7953	1.123	err	1.00	2.00	err	err
N[20]	NA	7924	1.244	err	1.00	2.00	err	err

p[1]

p[2]

p[3]

p[4]

p[5]

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[107]

N[12]

N[72]

N[21]

N[20]

model: fm2

jdt

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha	jdt	9422	-0.170	-0.153	-0.31	-0.04	0.14777	0.9777
alpha0	NA	4910	-2.524	-2.528	-2.73	-2.31	0	1.001
lambda[1]	NA	8915	0.581	0.491	0.24	0.91	0	1.001
lambda[2]	NA	7599	0.815	0.743	0.47	1.14	0	1.001
lambda[3]	NA	9506	0.927	0.832	0.52	1.30	0	1.001
lambda[4]	NA	7941	0.772	0.719	0.43	1.06	0	1.001
lambda[5]	NA	9235	0.330	0.288	0.13	0.51	0	1.001
N[115]	NA	10000	1.061	err	1.00	1.00	err	err
N[16]	NA	9629	0.103	err	0.00	0.00	err	err
N[61]	NA	10000	1.047	err	1.00	1.00	err	err
N[58]	NA	10000	1.054	err	1.00	1.00	err	err
N[47]	NA	9259	0.102	err	0.00	0.00	err	err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[115]

N[16]

N[61]

N[58]

N[47]

alpha relationship

model: fm3

lure

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha	lure	9489	-0.008	-0.022	-0.17	0.15	0.97272	0.5296
alpha0	NA	5189	-2.505	-2.496	-2.70	-2.29	0	1.001
lambda[1]	NA	9306	0.538	0.484	0.21	0.84	0	1.001
lambda[2]	NA	8281	0.826	0.735	0.47	1.15	0	1.001
lambda[3]	NA	9136	0.942	0.912	0.52	1.32	0	1.001
lambda[4]	NA	8953	0.763	0.714	0.45	1.06	0	1.001
lambda[5]	NA	8590	0.339	0.282	0.13	0.54	0	1.001
N[46]	NA	9660	1.508	1	1.00	2.00	0	1.0001
N[83]	NA	10143	0.136	err	0.00	1.00	err	err
N[47]	NA	8777	0.105	err	0.00	0.00	err	err
N[5]	NA	8795	1.828	2.002	1.00	3.00	0	1.0005
N[97]	NA	9238	0.026	err	0.00	0.00	err	err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[46]

N[83]

N[47]

N[5]

N[97]

alpha relationship

model: fm4

lure + jdt

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha[1]	lureDays	8616	0.067	0.077	-0.11	0.24	0.8109	0.7267
alpha[2]	julianDt	8670	-0.191	-0.213	-0.35	-0.05	0.12979	0.9817
alpha0	NA	4975	-2.521	-2.491	-2.74	-2.33	0	1.001
lambda[1]	NA	9012	0.602	0.497	0.23	0.93	0	1.001
lambda[2]	NA	8585	0.829	0.786	0.49	1.17	0	1.001
lambda[3]	NA	9022	0.927	0.863	0.53	1.32	0	1.001
lambda[4]	NA	8191	0.774	0.736	0.47	1.08	0	1.001
lambda[5]	NA	10000	0.325	0.272	0.12	0.51	0	1.001
N[77]	NA	10000	0.125	err	0.00	1.00	err	err
N[52]	NA	10000	0.044	err	0.00	0.00	err	err
N[58]	NA	10000	1.059	err	1.00	1.00	err	err
N[105]	NA	10000	1.030	err	1.00	1.00	err	err
N[127]	NA	9473	0.017	err	0.00	0.00	err	err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[77]

N[52]

N[58]

N[105]

N[127]

model: fm5

jdt + jdtSq

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha[1]	julianDt	4659	0.094	0.106	-0.12	0.35	0.89194	0.7388
alpha[2]	julianDtSq	4072	-0.382	-0.399	-0.64	-0.11	0.07627	0.9906
alpha0	NA	4605	-2.588	-2.581	-2.80	-2.37	0	1.001
lambda[1]	NA	9300	0.552	0.465	0.22	0.86	0	1.001
lambda[2]	NA	7575	0.888	0.849	0.51	1.22	0	1.001
lambda[3]	NA	7938	0.924	0.857	0.51	1.30	0	1.001
lambda[4]	NA	7826	0.834	0.769	0.49	1.16	0	1.001
lambda[5]	NA	10000	0.333	0.27	0.13	0.52	0	1.001
N[45]	NA	10000	1.674	1	1.00	3.00	0	1.0003
N[57]	NA	8748	2.367	2.002	2.00	4.00	0	1.0009
N[126]	NA	9377	0.019	err	0.00	0.00	err	err
N[32]	NA	10000	0.065	err	0.00	0.00	err	err
N[59]	NA	10000	0.051	err	0.00	0.00	err	err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[45]

N[57]

N[126]

N[32]

N[59]

julian date relationship

model: fm6

lure + jdt + jdtSq

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha[1]	lureDays	5900	-0.037	-0.037	-0.22	0.15	0.96177	0.6223
alpha[2]	julianDt	3266	0.115	0.078	-0.14	0.37	0.80197	0.7626
alpha[3]	julianDtSq	3316	-0.401	-0.399	-0.68	-0.13	0.07549	0.9893
alpha0	NA	4247	-2.593	-2.585	-2.80	-2.37	0	1.001
lambda[1]	NA	8777	0.545	0.475	0.22	0.86	0	1.001
lambda[2]	NA	7738	0.881	0.84	0.51	1.23	0	1.001
lambda[3]	NA	8437	0.918	0.885	0.53	1.30	0	1.001
lambda[4]	NA	7867	0.831	0.771	0.49	1.15	0	1.001
lambda[5]	NA	9498	0.339	0.276	0.13	0.53	0	1.001
N[78]	NA	10000	0.270	err	0.00	1.00	err	err
N[30]	NA	9420	1.359	1	1.00	2.00	0	1
N[42]	NA	9710	0.255	err	0.00	1.00	err	err
N[57]	NA	8810	2.341	2.002	2.00	4.00	0	1.0009
N[44]	NA	9480	0.360	0	0.00	1.00	1	err

alpha[1]

alpha[2]

alpha[3]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[78]

N[30]

N[42]

N[57]

N[44]

model: fm7

counts

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha	counts	8243	7.653	7.24	5.56	9.55	0	1.001
alpha0	NA	9596	-7.163	-6.841	-8.80	-5.59	0	1.001
lambda[1]	NA	8812	0.975	0.808	0.34	1.54	0	1.001
lambda[2]	NA	9695	0.982	0.907	0.56	1.36	0	1.001
lambda[3]	NA	10000	0.991	0.957	0.53	1.41	0	1.001
lambda[4]	NA	10000	0.988	0.94	0.55	1.40	0	1.001
lambda[5]	NA	7503	0.964	0.794	0.34	1.53	0	1.001
N[115]	NA	0	1.000	err	1.00	1.00	err	err
N[108]	NA	10000	1.000	err	1.00	1.00	err	err
N[86]	NA	0	1.000	err	1.00	1.00	err	err
N[99]	NA	0	1.000	err	1.00	1.00	err	err
N[110]	NA	10000	0.960	0	0.00	2.00	1	err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[115]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero

## Warning: Removed 50 rows containing missing values (geom_bar).

N[108]

N[86]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero

## Warning: Removed 50 rows containing missing values (geom_bar).

N[99]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero

## Warning: Removed 50 rows containing missing values (geom_bar).

N[110]

alpha relationship